IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v114y2018ipbp321-337.html
   My bibliography  Save this article

A random utility based estimation framework for the household activity pattern problem

Author

Listed:
  • Xu, Zhiheng
  • Kang, Jee Eun
  • Chen, Roger

Abstract

This paper develops a random utility based estimation framework for the Household Activity Pattern Problem (HAPP). Based on the realization that outputs of complex activity-travel decisions form a continuous pattern in space-time dimension, the estimation framework is treated as a pattern selection problem. In particular, we define a variant of HAPP that has capabilities of forecasting activity selection and durations in addition to activity sequencing. The framework is comprised of three steps, (i) choice set generation, (ii) choice set individualization and (iii) model estimation. The estimation results show that utilities for work, shopping and disutilities for travel time, time outside home, and average tour delay are found to be significant in activity-travel decision making.

Suggested Citation

  • Xu, Zhiheng & Kang, Jee Eun & Chen, Roger, 2018. "A random utility based estimation framework for the household activity pattern problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PB), pages 321-337.
  • Handle: RePEc:eee:transa:v:114:y:2018:i:pb:p:321-337
    DOI: 10.1016/j.tra.2018.01.036
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856417308996
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2018.01.036?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bliemer, Michiel C.J. & Rose, John M., 2010. "Construction of experimental designs for mixed logit models allowing for correlation across choice observations," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 720-734, July.
    2. Lothlorien Redmond & Patricia Mokhtarian, 2001. "The positive utility of the commute: modeling ideal commute time and relative desired commute amount," Transportation, Springer, vol. 28(2), pages 179-205, May.
    3. Arentze, Theo A. & Timmermans, Harry J. P., 2004. "A learning-based transportation oriented simulation system," Transportation Research Part B: Methodological, Elsevier, vol. 38(7), pages 613-633, August.
    4. Bowman, J. L. & Ben-Akiva, M. E., 2001. "Activity-based disaggregate travel demand model system with activity schedules," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 1-28, January.
    5. W C Wilson, 1998. "Activity Pattern Analysis by Means of Sequence-Alignment Methods," Environment and Planning A, , vol. 30(6), pages 1017-1038, June.
    6. Recker, Will W & Duan, J. & Wang, H., 2008. "Development of an estimation procedure for an activity-based travel demand model," University of California Transportation Center, Working Papers qt0rz778v6, University of California Transportation Center.
    7. David Charypar & Kai Nagel, 2005. "Generating complete all-day activity plans with genetic algorithms," Transportation, Springer, vol. 32(4), pages 369-397, July.
    8. Chow, Joseph Y.J. & Recker, Will W., 2012. "Inverse optimization with endogenous arrival time constraints to calibrate the household activity pattern problem," Transportation Research Part B: Methodological, Elsevier, vol. 46(3), pages 463-479.
    9. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    10. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    11. Gan, Li Ping & Recker, Will, 2008. "A mathematical programming formulation of the household activity rescheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 42(6), pages 571-606, July.
    12. Shlomo Bekhor & Moshe Ben-Akiva & M. Ramming, 2006. "Evaluation of choice set generation algorithms for route choice models," Annals of Operations Research, Springer, vol. 144(1), pages 235-247, April.
    13. Joh, Chang-Hyeon & Arentze, Theo & Hofman, Frank & Timmermans, Harry, 2002. "Activity pattern similarity: a multidimensional sequence alignment method," Transportation Research Part B: Methodological, Elsevier, vol. 36(5), pages 385-403, June.
    14. Recker, W. W., 1995. "The household activity pattern problem: General formulation and solution," Transportation Research Part B: Methodological, Elsevier, vol. 29(1), pages 61-77, February.
    15. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    16. Abdul Rawoof Pinjari & Chandra R. Bhat, 2011. "Activity-based Travel Demand Analysis," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 10, Edward Elgar Publishing.
    17. Li Ping Gan & Will Recker, 2013. "Stochastic Preplanned Household Activity Pattern Problem with Uncertain Activity Participation (SHAPP)," Transportation Science, INFORMS, vol. 47(3), pages 439-454, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Usman Ahmed & Ana Tsui Moreno & Rolf Moeckel, 2021. "Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes," Transportation, Springer, vol. 48(3), pages 1481-1502, June.
    2. Weijia (Vivian) Li & Kara M. Kockelman, 2022. "How does machine learning compare to conventional econometrics for transport data sets? A test of ML versus MLE," Growth and Change, Wiley Blackwell, vol. 53(1), pages 342-376, March.
    3. Usman Ahmed & Ana Tsui Moreno & Rolf Moeckel, 0. "Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes," Transportation, Springer, vol. 0, pages 1-22.
    4. Yashar Khayati & Jee Eun Kang & Mark Karwan & Chase Murray, 2021. "Household Activity Pattern Problem with Autonomous Vehicles," Networks and Spatial Economics, Springer, vol. 21(3), pages 609-637, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Arentze, Theo A. & Ettema, Dick & Timmermans, Harry J.P., 2011. "Estimating a model of dynamic activity generation based on one-day observations: Method and results," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 447-460, February.
    2. Staffan Algers & Jonas Eliasson & Lars-Göran Mattsson, 2005. "Is it time to use activity-based urban transport models? A discussion of planning needs and modelling possibilities," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 39(4), pages 767-789, December.
    3. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    4. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    5. Tapia, Rodrigo J. & Kourounioti, Ioanna & Thoen, Sebastian & de Bok, Michiel & Tavasszy, Lori, 2023. "A disaggregate model of passenger-freight matching in crowdshipping services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    6. Chiara Mazzocchi & Guido Sali, 2022. "Supporting mountain agriculture through “mountain product” label: a choice experiment approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 701-723, January.
    7. Batarce, Marco & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2016. "Valuing crowding in public transport: Implications for cost-benefit analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 358-378.
    8. Larranaga, Ana Margarita & Arellana, Julian & Senna, Luiz Afonso, 2017. "Encouraging intermodality: A stated preference analysis of freight mode choice in Rio Grande do Sul," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 202-211.
    9. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2011. "Individually adapted sequential Bayesian conjoint-choice designs in the presence of consumer heterogeneity," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 378-388.
    10. Wang, Yihong & Correia, Gonçalo Homem de Almeida & de Romph, Erik & Timmermans, H.J.P., 2017. "Using metro smart card data to model location choice of after-work activities: An application to Shanghai," Journal of Transport Geography, Elsevier, vol. 63(C), pages 40-47.
    11. Chiara Mazzocchi & Luigi Orsi & Guido Sali, 2021. "Consumers’ Attitudes for Sustainable Mountain Cheese," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    12. Ana I. Sanjuán‐López & Helena Resano‐Ezcaray, 2020. "Labels for a Local Food Speciality Product: The Case of Saffron," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 778-797, September.
    13. Nguyen, Ly & Gao, Zhifeng & Anderson, James L., 2022. "Regulating menu information: What do consumers care and not care about at casual and fine dining restaurants for seafood consumption?," Food Policy, Elsevier, vol. 110(C).
    14. Grigolon, Anna B. & Borgers, Aloys W.J. & Kemperman, Astrid D.A.M. & Timmermans, Harry J.P., 2014. "Vacation length choice: A dynamic mixed multinomial logit model," Tourism Management, Elsevier, vol. 41(C), pages 158-167.
    15. Hong, Sung-Pil & Kim, Kyung min & Byeon, Geunyeong & Min, Yun-Hong, 2017. "A method to directly derive taste heterogeneity of travellers’ route choice in public transport from observed routes," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 41-52.
    16. Rose, John M. & Bliemer, Michiel C.J. & Hensher, David A. & Collins, Andrew T., 2008. "Designing efficient stated choice experiments in the presence of reference alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 395-406, May.
    17. Sriwastava, Ambuj & Reichert, Peter, 2023. "Reducing sample size requirements by extending discrete choice experiments to indifference elicitation," Journal of choice modelling, Elsevier, vol. 48(C).
    18. Joseph F. Wyer, 2018. "Urban Transportation Mode Choice And Trip Complexity: Bicyclists Stick To Their Gears," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1777-1787, July.
    19. Abdul Rawoof Pinjari & Chandra R. Bhat, 2011. "Activity-based Travel Demand Analysis," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 10, Edward Elgar Publishing.
    20. Bliemer, Michiel C.J. & Rose, John M. & Hensher, David A., 2009. "Efficient stated choice experiments for estimating nested logit models," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 19-35, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:114:y:2018:i:pb:p:321-337. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.